Why is My AI Memory Always Full? Understanding ChatGPT and Claude Memory Limits

What Does "Memory Full" Actually Mean?

It happens with every AI service I use on a regular basis. They all mention the same issue: "Memory Full", or at least their distinctive, top center of screen message says so, for the ones that have it. To which you may ask: what memory?

We all know these companies thrive on the data we give them. It has been that way since targeted ads became the bread and butter for most "free" products out there (as the saying goes: if a certain product is free, you are the currency). So, are they pulling a reverse Facebook and actually letting us know what information they have on us? Not really. We know they use our data for training these beefy models (even if you tick the available privacy boxes it is hard to trust that our data is not used for training purposes), so why would they provide us with an information regarding our memory being full?

It is a fair question, but I am afraid the answer is not as straight forward. Let me break it down for you.

Why Do AI Assistants Need Memory in the First Place?

If you used an AI model without any context about you, the answers are usually... generic. Hence, adding a bit more context, for example, through a master prompt, already improves the responses quite a bit. But of course, most likely your master prompt has some shortcomings. It will be incomplete, and these AI services use the history of previous conversations with you to figure out the missing pieces of the puzzle and prepare the best prompt possible to you, because to them, this means you are more likely to use their models, and when you use them more, you are more likely to pay (or pay even more for the higher tiers).

And, now going in a bit of a hypothetical tangent, they also get more data for training their new models, possibly giving them an edge over the competition. Now, I am not an expert by no means in model training, so I will leave this one as a guess. I am pretty sure using our data would still require a bit more processing before it is usable, but with AI models, "everything" is possible, and there must be a reason these services include A/B testing for prompts (in the form of "which prompt do you like better?", commonly seen in ChatGPT) and session ratings ("How is Claude Doing In This Session?", right inside Claude Code). This information is only useful for them on a "YDIL" setup (Your Data In the Loop). I know, I might regret it if I do not trademark that acronym someday.

Alright, now that we know our data is very useful for AI services, the next question is: what do they store in this memory?

What Information Does ChatGPT and Claude Store About You?

To figure this out, I have to admit it: I went with the simplest option. When you do not know something: ask. So, I went to ChatGPT and asked it what is stored in this memory. I will not quote it, because that would be... strange, but in essence, it is a collection of facts about you. What you do, what you want to do, what your skills are, what you enjoy, what you do not like... some might argue it is a pretty comprehensive description of what is on your mind. And then it feeds these information as context when appropriate, referencing it depending on where your conversations go.

You can perform a simple test to see it in action: ask a question of some topic you may have chatted about in the last conversation you had and then activate the incognito mode and use the same exact prompt. The results are different, right? But you might argue: "That's expected. Even if I use the same prompt in non-incognito I will get a different response". The key is in the generalization of the response: what you see when using the incognito more is a way more generic response, while the ones created directly within your account seem more geared towards the same response, based on, you guessed it, on what the AI service knows about you.

The Hidden Drawbacks of AI Memory Storage

Now, we know that AI companies store information about you to directly influence its responses (keep in mind, they may have more information, their inner workings are not open source) and improve the quality of the responses given to you, so that, with better context, you may stick around longer with one service in detriment of another. This is, of course, a big plus, everyone wants to receive the best response possible to their problems! But it does come with its drawbacks.

For the sake of staying away from arguments like "creepy", "invasion of privacy" and others, remember: you use their services because you want to. So, these are not valid arguments as drawbacks, unless, that is, they do not make it extremely visible they have your data. Here, I will not be the judge, although I think they could make better efforts in that regard. Nothing other tech companies have not gotten us used to, right?

I have two main disadvantages to outline: vendor lock-in and memory limitations.

AI Vendor Lock-In Through Memory

For the vendor lock-in, it is obvious: the model you use the most will likely always be perceived as the best one for the regular user, unless it gets completely blown out of the water. Therefore, you need to take memory into consideration when hearing the opinions of others mentioning model A is better than model B, because their preferred model has this unfair advantage. It is not an apples-to-apples benchmark.

How to Manage AI Memory Limits

Regarding memory limits, these models have very limited memory, and it would be quite useful to have control over it. There is not an easy way to trim, delete, and edit the memory it has stored about you, resulting sometimes in outdated information. My ChatGPT memory still briefly mentions projects that I have not pursued since one year ago. That is incredibly dumb, but, what else should we expect from AI?

Building Your Own AI Memory System

In my post Stop Being Nice to Your AI (Build an Accountability System Instead) (opens in a new tab) I go into detail on how you can build your own AI memory from scratch, with easy maintenance, data ownership and build upon what these AI services store, leading to better prompts, more geared towards your needs, and, most importantly, detach the memory from a specific AI model.

Building in public. Follow my journey at InvisiblePuzzle (opens in a new tab) where I document how I'm building B2B automation tools while working full-time.

Tags: #ai #claude #chatgpt #memory